Many robots are electro-mechanical machines, which are controlled by a computer. Mobile robots have the capability to move around in their environment and are not fixed to one physical location. An example of a mobile robot that is in common use today is an automated guided vehicle or automatic guided vehicle (AGV). An AGV is typically considered to be a mobile robot that follows markers or wires in the floor, or uses a vision system or lasers for navigation. Mobile robots can be found in industry, military and security environments. They also appear as consumer products, for entertainment or to perform specific tasks such as vacuum cleaning and home assistance.
Machine learning is a subfield of computer science and artificial intelligence that deals with the construction of systems that can learn or be trained from data. Machine learning can involve performing a class of processes referred to as supervised learning in which a classifier is trained using a set of ground truth training data. This ground truth training data provides example inputs and the desired outputs. In many instances, the goal of a machine learning process is to train a classifier that is able to determine a rule or set of rules that maps the inputs to the appropriate outputs. For example, in order to train a handwriting recognition classifier, the training data may include handwritten characters as inputs and the outputs would specify the actual characters that should be recognized by the classifier for the input handwritten characters. Accordingly, supervised learning processes attempt to use a function or mapping learned from a training set of inputs and outputs to generate an output for previously unseen inputs.